dc.contributor.author |
Yu, Gang
|
|
dc.contributor.author |
Ye, Xianming
|
|
dc.contributor.author |
Ye, Yuxiang
|
|
dc.contributor.author |
Huang, Hongxu
|
|
dc.contributor.author |
Xia, Xiaohua
|
|
dc.date.accessioned |
2025-03-20T11:56:06Z |
|
dc.date.available |
2025-03-20T11:56:06Z |
|
dc.date.issued |
2024-09 |
|
dc.description |
DATA AVAILABILITY : Data will be made available on request. |
en_US |
dc.description.abstract |
The fossil fuel powered mining truck fleets can contribute up to 80% of total emissions in open pit
mines. This study investigates the optimal decarbonisation pathway for mining truck fleets. Notably, our
proposed pathway incorporates power generation, negative carbon technologies, and carbon trading. Technical,
financial, and environmental models of decarbonisation technologies are established, capturing regional
variations and time dynamic characteristics such as cost trends and carbon capture efficiency. The dynamic
natures of characteristics pose challenges for using the cost-effective analyses approach to find the optimal
decarbonisation pathway. To address this, we introduce a mixed-integer programming optimisation framework
to find the decarbonisation pathway with minimum life cycle costs during the planning period. A case study for
the optimal decarbonisation pathway of truck fleets in a South African coal mine is conducted to illustrate the
applicability of the proposed model. Results indicate that the optimal decarbonisation pathway is significantly
influenced by factors such as land cost, annual budget, and carbon trading prices. The proposed method
provides invaluable guidance for transitioning towards a cleaner and more sustainable mining industry. |
en_US |
dc.description.department |
Electrical, Electronic and Computer Engineering |
en_US |
dc.description.librarian |
am2024 |
en_US |
dc.description.sdg |
SDG-07:Affordable and clean energy |
en_US |
dc.description.sdg |
SDG-09: Industry, innovation and infrastructure |
en_US |
dc.description.sdg |
SDG-12:Responsible consumption and production |
en_US |
dc.description.sponsorship |
National Key R&D Program of China, National Natural Science Foundation of China, National Research Foundation China/South Africa Research Cooperation Programme and Royal Academy of Engineering Transforming Systems through Partnership grant scheme. |
en_US |
dc.description.uri |
www.keaipublishing.com/en/journals/journal-of-automation-and-intelligence/ |
en_US |
dc.identifier.citation |
Yu, G., Ye, X., Ye, Y. et al. 2024, 'Optimal decarbonisation pathway for mining truck fleets', Journal of Automation and Intelligence, vol. 3, pp. 129-143.
https://DOI.org/10.1016/j.jai.2024.03.003. |
en_US |
dc.identifier.issn |
2949-8554 |
|
dc.identifier.other |
10.1016/j.jai.2024.03.003 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/101628 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
KeAi Communications |
en_US |
dc.rights |
© 2024 The Authors.
This is an open access article under the CC BY-NC-ND
license. |
en_US |
dc.subject |
Coal mine |
en_US |
dc.subject |
Truck fleet |
en_US |
dc.subject |
Carbon emission |
en_US |
dc.subject |
Optimal decarbonisation pathway |
en_US |
dc.subject |
SDG-07: Affordable and clean energy |
en_US |
dc.subject |
SDG-09: Industry, innovation and infrastructure |
en_US |
dc.subject |
SDG-12: Responsible consumption and production |
en_US |
dc.title |
Optimal decarbonisation pathway for mining truck fleets |
en_US |
dc.type |
Article |
en_US |